Gene Editing Technology Platform

ClimateEdit™ Platform

Precision Engineering at Scale

The ClimateEdit Platform is ClimateCrop's proprietary end-to-end gene editing pipeline. It integrates target identification, guide RNA design, delivery optimisation, event selection, and field validation into a single streamlined workflow that takes candidate traits from computer model to commercial seed in under four years.

Unlike first-generation GMO approaches that insert foreign genes, ClimateEdit works exclusively with the crop's own genome — making single nucleotide changes, small insertions or deletions, or targeted regulatory modifications that mimic natural allelic variation. This SDN-1 and SDN-2 edit strategy positions our varieties favourably in rapidly evolving global regulatory frameworks.

Our computational genomics infrastructure processes over 10 terabases of reference genome data, enabling us to identify high-value target loci with unmatched precision. Each guide RNA design is validated in silico against thousands of off-target sites before any laboratory work begins.

CRISPR-Cas9 Base Editing Prime Editing SDN-1 / SDN-2 RNP Delivery

Three Editing Technologies, One Platform

Each tool in our platform is chosen for the specific edit type required — maximising precision and minimising off-target risk.

CRISPR-Cas9

Our core editing tool for loss-of-function and targeted integration applications. We use high-fidelity Cas9 variants with engineered PAM recognition to minimise off-target events while maintaining high on-target efficiency across monocot and dicot crop species.

High-fidelity Cas9 for off-target minimisation
Proprietary RNP delivery — no transgene integration
Applicable to 12+ crop species
On-target efficiency routinely above 85%

Base Editing

Cytosine base editors (CBEs) and adenine base editors (ABEs) introduce specific point mutations without double-strand DNA breaks, dramatically reducing chromosomal rearrangement risk. Ideal for introducing alleles from natural variation that confer stress tolerance.

C→T and A→G conversions without DNA breaks
Introduces natural stress-tolerance alleles precisely
Lower off-target profile vs. nuclease editing
Ideal for regulatory-favourable SDN-2 applications

Prime Editing

Prime editing expands our capability beyond simple point mutations, enabling targeted insertions up to several hundred base pairs and all twelve types of point mutations without donor DNA templates. Proprietary pegRNA optimisation algorithms achieve 3–5× above published benchmarks in cereal crops.

All 12 point mutation types addressable
Targeted insertions without donor template
Proprietary pegRNA optimisation algorithm
3–5× efficiency improvement over academic benchmarks

From Discovery to Field

Our six-stage development pipeline takes a candidate trait from genomic data to a licensed commercial variety in under four years — roughly half the time of conventional gene-discovery-to-market processes.

1

Trait Discovery & Target Identification

Computational genomics analysis of thousands of landraces and wild crop relatives identifies natural genetic variants associated with climate stress tolerance. Machine learning models prioritise targets by predicted efficacy and regulatory risk. Our proprietary CropGenome database holds over 2 million annotated trait associations.

2

Guide RNA Design & In Silico Validation

Automated pipelines evaluate all candidate protospacer sequences for on-target efficiency, off-target binding risk, and secondary structure conflicts. Only guides achieving a composite ClimateScore above threshold proceed to laboratory work. This filter eliminates over 90% of candidates before any wet lab begins.

3

Cell & Tissue Culture Editing

Validated guide RNAs are delivered to immature embryos or callus tissue of elite breeding lines via biolistics, Agrobacterium, or direct RNP protoplast transfection depending on species and edit type. Our regeneration protocols have been optimised for recalcitrant monocots including wheat, rice, maize, and sorghum.

4

Event Selection & Molecular Characterisation

T0 regenerants are screened by amplicon sequencing to identify events carrying the desired edit. Whole-genome sequencing confirms edit precision and absence of off-target changes. Selected events are backcrossed to elite germplasm to move edits into elite genetic backgrounds.

5

Controlled Environment & Field Validation

Edited lines undergo rigorous phenotypic evaluation beginning with controlled environment stress trials, progressing through multi-location field trials under managed stress conditions, and culminating in commercial-scale agronomic trials with seed company partners. Three years of field data required before licensing.

6

Regulatory Filing & Commercialisation

Our regulatory team prepares comprehensive dossiers for USDA APHIS regulatory status requests and international equivalents. ClimateCrop has achieved favourable determinations for all varieties submitted to date. Commercialisation through licensing to global seed companies and public research institutions.

Platform Capabilities

The ClimateEdit Platform is designed to be a complete end-to-end solution from data to field.

Computational Genomics

10+ terabases of reference genome data powering target discovery.

Multi-Crop Delivery

Optimised transformation protocols for 12+ monocot and dicot species.

WGS Event Characterisation

Whole-genome sequencing confirms precision and absence of off-target events.

Global Regulatory Strategy

100% regulatory approval rate across all varieties submitted to date.

CropGenome — Our Proprietary Database

At the foundation of the ClimateEdit Platform is CropGenome, a curated database of over 2 million annotated trait associations across major cereal and legume species. Built from reanalysis of thousands of published and proprietary sequencing datasets, CropGenome enables us to identify the most promising targets for climate stress tolerance with a precision that no publicly available resource can match.

2M+ Trait Associations

Curated associations spanning cereal and legume crops across stress environments.

ML-Powered Prioritisation

Machine learning models rank targets by predicted efficacy and regulatory risk before any wet lab investment.

10+ Terabases Reference Data

Comprehensive genomic reference set enabling off-target prediction across all target crop species.

Our Gene Editing Technology Platform